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authorvrouvrea <vrouvrea@636b058d-ea47-450e-bf9e-a15bfbe3eedb>2016-12-01 16:42:46 +0000
committervrouvrea <vrouvrea@636b058d-ea47-450e-bf9e-a15bfbe3eedb>2016-12-01 16:42:46 +0000
commit58c77ecd1c09c1cf116be44c1a7e9d18cd99970b (patch)
tree58e0c560a96a18c2956384ab85936e70f4606a76
parent0349fb45a621bc1af4d3505cbe7bb13ebaf89f12 (diff)
Remove traces from tangential
Tests the limits for choose_n_farthest_points and fix random git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/trunk@1808 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: 53eec1efbc138080d1b202c2cdd4e7ff8cdde266
-rw-r--r--src/Subsampling/include/gudhi/choose_n_farthest_points.h20
-rw-r--r--src/Subsampling/test/test_choose_n_farthest_points.cpp55
-rw-r--r--src/Tangential_complex/include/gudhi/Tangential_complex/config.h3
3 files changed, 67 insertions, 11 deletions
diff --git a/src/Subsampling/include/gudhi/choose_n_farthest_points.h b/src/Subsampling/include/gudhi/choose_n_farthest_points.h
index 40c7808d..9b45c640 100644
--- a/src/Subsampling/include/gudhi/choose_n_farthest_points.h
+++ b/src/Subsampling/include/gudhi/choose_n_farthest_points.h
@@ -60,10 +60,15 @@ void choose_n_farthest_points(Kernel const &k,
std::size_t final_size,
std::size_t starting_point,
OutputIterator output_it) {
- typename Kernel::Squared_distance_d sqdist = k.squared_distance_d_object();
-
std::size_t nb_points = boost::size(input_pts);
- assert(nb_points >= final_size);
+ if (final_size > nb_points)
+ final_size = nb_points;
+
+ // Tests to the limit
+ if (final_size < 1)
+ return;
+
+ typename Kernel::Squared_distance_d sqdist = k.squared_distance_d_object();
std::size_t current_number_of_landmarks = 0; // counter for landmarks
const double infty = std::numeric_limits<double>::infinity(); // infinity (see next entry)
@@ -107,11 +112,16 @@ void choose_n_farthest_points(Kernel const& k,
Point_container const &input_pts,
unsigned final_size,
OutputIterator output_it) {
+ // Tests to the limit
+ if ((final_size < 1) || (input_pts.size() == 0))
+ return;
+
// Choose randomly the first landmark
std::random_device rd;
std::mt19937 gen(rd());
- std::uniform_int_distribution<> dis(1, 6);
- int starting_point = dis(gen);
+ std::uniform_int_distribution<> dis(0, (input_pts.size() - 1));
+ std::size_t starting_point = dis(gen);
+
choose_n_farthest_points(k, input_pts, final_size, starting_point, output_it);
}
diff --git a/src/Subsampling/test/test_choose_n_farthest_points.cpp b/src/Subsampling/test/test_choose_n_farthest_points.cpp
index d064899a..0bc0dff4 100644
--- a/src/Subsampling/test/test_choose_n_farthest_points.cpp
+++ b/src/Subsampling/test/test_choose_n_farthest_points.cpp
@@ -39,18 +39,65 @@ typedef CGAL::Epick_d<CGAL::Dynamic_dimension_tag> K;
typedef typename K::FT FT;
typedef typename K::Point_d Point_d;
-BOOST_AUTO_TEST_CASE(test_choose_farthest_point) {
+typedef boost::mpl::list<CGAL::Epick_d<CGAL::Dynamic_dimension_tag>, CGAL::Epick_d<CGAL::Dimension_tag<4>>> list_of_tested_kernels;
+
+BOOST_AUTO_TEST_CASE_TEMPLATE(test_choose_farthest_point, Kernel, list_of_tested_kernels) {
+ typedef typename Kernel::FT FT;
+ typedef typename Kernel::Point_d Point_d;
std::vector< Point_d > points, landmarks;
// Add grid points (625 points)
for (FT i = 0; i < 5; i += 1.0)
for (FT j = 0; j < 5; j += 1.0)
for (FT k = 0; k < 5; k += 1.0)
- for (FT l = 0; l < 5; l += 1.0)
- points.push_back(Point_d(std::vector<FT>({i, j, k, l})));
+ for (FT l = 0; l < 5; l += 1.0) {
+ std::vector<FT> point({i, j, k, l});
+ points.push_back(Point_d(point.begin(), point.end()));
+ }
landmarks.clear();
- K k;
+ Kernel k;
Gudhi::subsampling::choose_n_farthest_points(k, points, 100, std::back_inserter(landmarks));
BOOST_CHECK(landmarks.size() == 100);
+ for (auto landmark : landmarks)
+ {
+ // Check all landmarks are in points
+ BOOST_CHECK(std::find (points.begin(), points.end(), landmark) != points.end());
+ }
+}
+
+BOOST_AUTO_TEST_CASE_TEMPLATE(test_choose_farthest_point_limits, Kernel, list_of_tested_kernels) {
+ typedef typename Kernel::FT FT;
+ typedef typename Kernel::Point_d Point_d;
+ std::vector< Point_d > points, landmarks;
+ landmarks.clear();
+ Kernel k;
+ // Choose -1 farthest points in an empty point cloud
+ Gudhi::subsampling::choose_n_farthest_points(k, points, -1, std::back_inserter(landmarks));
+ BOOST_CHECK(landmarks.size() == 0);
+ landmarks.clear();
+ // Choose 0 farthest points in an empty point cloud
+ Gudhi::subsampling::choose_n_farthest_points(k, points, 0, std::back_inserter(landmarks));
+ BOOST_CHECK(landmarks.size() == 0);
+ landmarks.clear();
+ // Choose 1 farthest points in an empty point cloud
+ Gudhi::subsampling::choose_n_farthest_points(k, points, 1, std::back_inserter(landmarks));
+ BOOST_CHECK(landmarks.size() == 0);
+ landmarks.clear();
+
+ std::vector<FT> point({0.0, 0.0, 0.0, 0.0});
+ points.push_back(Point_d(point.begin(), point.end()));
+ // Choose -1 farthest points in an empty point cloud
+ Gudhi::subsampling::choose_n_farthest_points(k, points, -1, std::back_inserter(landmarks));
+ BOOST_CHECK(landmarks.size() == 1);
+ landmarks.clear();
+ // Choose 0 farthest points in a one point cloud
+ Gudhi::subsampling::choose_n_farthest_points(k, points, 0, std::back_inserter(landmarks));
+ BOOST_CHECK(landmarks.size() == 0);
+ landmarks.clear();
+ // Choose 1 farthest points in a one point cloud
+ Gudhi::subsampling::choose_n_farthest_points(k, points, 1, std::back_inserter(landmarks));
+ BOOST_CHECK(landmarks.size() == 1);
+ landmarks.clear();
+
}
diff --git a/src/Tangential_complex/include/gudhi/Tangential_complex/config.h b/src/Tangential_complex/include/gudhi/Tangential_complex/config.h
index 98a1b14f..ffefcd6b 100644
--- a/src/Tangential_complex/include/gudhi/Tangential_complex/config.h
+++ b/src/Tangential_complex/include/gudhi/Tangential_complex/config.h
@@ -26,8 +26,7 @@
#include <cstddef>
// ========================= Debugging & profiling =============================
-#define GUDHI_TC_PROFILING
-#define DEBUG_TRACES
+// #define GUDHI_TC_PROFILING
// #define GUDHI_TC_VERY_VERBOSE
// #define GUDHI_TC_PERFORM_EXTRA_CHECKS
// #define GUDHI_TC_SHOW_DETAILED_STATS_FOR_INCONSISTENCIES